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Author: search.filters.author.Gupta, RajivSubject: search.filters.subject.SARS-CoV-2

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    Trade-off between Safety of Construction Workers and Economy in Backdrop of Covid-19
    (IAAM-VBRI Press, 2020) Gupta, Rajiv
    The Indian Construction industry, which contributes to 8-10% of the country's GDP, is suffering from an unprecedented crisis in the wake of the COVID-19 pandemic. The Indian Government is facing a strict trade-off between preventing and containing the spread of Coronavirus on the one hand and revitalizing the economic activities which have come to complete halt/resumed partially depending on the zone to which an area depends on the other side. Impact of the lockdown on the industry, stimulus measures announced by the Indian Government, and some other actions recommended by Industry experts' for the revival of the Construction sector are discussed in this paper. The detailed specific guidelines to be adopted by the site personnel for safely resuming the site work are presented for the benefit of Industry practitioners. Experimental study results on the stability of SARS-CoV-2 virus on surfaces of different materials are presented. Also, the potential and suitability of Construction material and technology for overcoming the current challenges posed by the pandemic is discussed. The main objective of the paper is to understand the current precarious situation of the Construction industry and the strategies to overcome it for moving forward.
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    ARIMA and NAR based prediction model for time series analysis of COVID-19 cases in India
    (Elsiever, 2020-09) Gupta, Rajiv
    In this paper, we have applied the univariate time series model to predict the number of COVID-19 infected cases that can be expected in upcoming days in India. We adopted an Auto-Regressive Integrated Moving Average (ARIMA) model on the data collected from 31st January 2020 to 25th March 2020 and verified it using the data collected from 26th March 2020 to 04th April 2020. A nonlinear autoregressive (NAR) neural network was developed to compare the accuracy of predicted models. The model has been used for daily prediction of COVID-19 cases for next 50 days without any additional intervention. Statistics from various sources, including the Ministry of Health and Family Welfare (MoHFW) and http://covid19india.org/ are used for the study. The results showed an increasing trend in the actual and forecasted numbers of COVID-19 cases with approximately 1500 cases per day, based on available data as on 04th April 2020. The appropriate ARIMA (1,1,0) model was selected based on the Bayesian Information Criteria (BIC) values and the overall highest R2 values of 0.95. The NAR model architecture constitutes ten neurons, which was optimized using the Levenberg-Marquardt optimization training algorithm (LM) with the overall highest R2 values of 0.97.